My three favorite introductory resources to Machine Learning
“Machine Learning” Coursera course by Andrew Ng (link)
This is the canonical best introduction to machine learning. It’s recommended by most and is a top choice for introduction to ML even in some FAANG some companies.
The course covers supervised learning (including linear regression and logistic regression along with neural networks) and unsupervised learning (including k-means, PCA analysis,). This course is heavier on math but well worth the effort.
100 Page Machine Learning Book by Andriv Burkov (link)
This is most concise introduction to machine learning in book form that I have found. So concise that its great for both students and professionals starting out and for higher level understanding for managers and executives.
Friendly Introduction to Machine Learning by Luis Serrano (link)
Luis Serrano is one of the few teachers that can drop down to a beginners mind and explain concepts from the ground up. This YouTube video and others from the author also use incredible animations to introduce topics such as mean squared error.
Incredible intuition on the idea of a “perceptron” (link)
INCREDIBLE visual introduction to machine learning (link)
Google Machine Learning Crash Course (link)
Elements of AI (link)
Tensorflow playground to get a sense of how neural network weights are being trained (link)